Paper: NILC_USP: Aspect Extraction using Semantic Labels

ACL ID S14-2075
Title NILC_USP: Aspect Extraction using Semantic Labels
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This paper details the system NILC USP that participated in the Semeval 2014: As- pect Based Sentiment Analysis task. This system uses a Conditional Random Field (CRF) algorithm for extracting the aspects mentioned in the text. Our work added se- mantic labels into a basic feature set for measuring the efficiency of those for as- pect extraction. We used the semantic roles and the highest verb frame as fea- tures for the machine learning. Overall, our results demonstrated that the system could not improve with the use of this se- mantic information, but its precision was increased.